Overview

Dataset statistics

Number of variables16
Number of observations26419
Missing cells94085
Missing cells (%)22.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 MiB
Average record size in memory128.0 B

Variable types

Numeric15
Categorical1

Alerts

driverId is highly overall correlated with raceId and 1 other fieldsHigh correlation
fastestLap is highly overall correlated with lapsHigh correlation
fastestLapSpeed is highly overall correlated with millisecondsHigh correlation
grid is highly overall correlated with position and 1 other fieldsHigh correlation
laps is highly overall correlated with fastestLap and 1 other fieldsHigh correlation
milliseconds is highly overall correlated with fastestLapSpeedHigh correlation
points is highly overall correlated with position and 3 other fieldsHigh correlation
position is highly overall correlated with grid and 5 other fieldsHigh correlation
positionOrder is highly overall correlated with laps and 5 other fieldsHigh correlation
positionText is highly overall correlated with position and 1 other fieldsHigh correlation
raceId is highly overall correlated with driverId and 1 other fieldsHigh correlation
rank is highly overall correlated with grid and 4 other fieldsHigh correlation
resultId is highly overall correlated with driverId and 1 other fieldsHigh correlation
statusId is highly overall correlated with points and 3 other fieldsHigh correlation
position has 10917 (41.3%) missing valuesMissing
positionText has 9015 (34.1%) missing valuesMissing
milliseconds has 18942 (71.7%) missing valuesMissing
fastestLap has 18478 (69.9%) missing valuesMissing
rank has 18249 (69.1%) missing valuesMissing
fastestLapSpeed has 18478 (69.9%) missing valuesMissing
resultId is uniformly distributedUniform
resultId has unique valuesUnique
grid has 1627 (6.2%) zerosZeros
points has 18419 (69.7%) zerosZeros
laps has 2519 (9.5%) zerosZeros

Reproduction

Analysis started2024-06-24 23:55:57.154297
Analysis finished2024-06-24 23:57:08.173529
Duration1 minute and 11.02 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

resultId
Real number (ℝ)

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct26419
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13210.926
Minimum1
Maximum26424
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:08.368601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1321.9
Q16605.5
median13210
Q319814.5
95-th percentile25103.1
Maximum26424
Range26423
Interquartile range (IQR)13209

Descriptive statistics

Standard deviation7627.9288
Coefficient of variation (CV)0.57739548
Kurtosis-1.1998307
Mean13210.926
Median Absolute Deviation (MAD)6605
Skewness0.00034662031
Sum3.4901944 × 108
Variance58185298
MonotonicityNot monotonic
2024-06-24T23:57:08.663364image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
17610 1
 
< 0.1%
17620 1
 
< 0.1%
17619 1
 
< 0.1%
17618 1
 
< 0.1%
17617 1
 
< 0.1%
17616 1
 
< 0.1%
17615 1
 
< 0.1%
17614 1
 
< 0.1%
17613 1
 
< 0.1%
Other values (26409) 26409
> 99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
26424 1
< 0.1%
26423 1
< 0.1%
26422 1
< 0.1%
26421 1
< 0.1%
26420 1
< 0.1%
26419 1
< 0.1%
26418 1
< 0.1%
26417 1
< 0.1%
26416 1
< 0.1%
26415 1
< 0.1%

raceId
Real number (ℝ)

HIGH CORRELATION 

Distinct1108
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean544.16746
Minimum1
Maximum1127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:09.175161image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile63
Q1297
median525
Q3800
95-th percentile1057
Maximum1127
Range1126
Interquartile range (IQR)503

Descriptive statistics

Standard deviation308.13475
Coefficient of variation (CV)0.56624987
Kurtosis-1.0589833
Mean544.16746
Median Absolute Deviation (MAD)250
Skewness0.11543094
Sum14376360
Variance94947.025
MonotonicityNot monotonic
2024-06-24T23:57:09.660872image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
800 55
 
0.2%
809 47
 
0.2%
368 39
 
0.1%
363 39
 
0.1%
357 39
 
0.1%
359 39
 
0.1%
360 39
 
0.1%
744 39
 
0.1%
371 39
 
0.1%
370 39
 
0.1%
Other values (1098) 26005
98.4%
ValueCountFrequency (%)
1 20
0.1%
2 20
0.1%
3 20
0.1%
4 20
0.1%
5 20
0.1%
6 20
0.1%
7 20
0.1%
8 20
0.1%
9 20
0.1%
10 20
0.1%
ValueCountFrequency (%)
1127 20
0.1%
1126 20
0.1%
1125 20
0.1%
1124 20
0.1%
1123 19
0.1%
1122 20
0.1%
1121 20
0.1%
1120 20
0.1%
1119 20
0.1%
1118 20
0.1%

driverId
Real number (ℝ)

HIGH CORRELATION 

Distinct859
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean272.54158
Minimum1
Maximum860
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:10.129344image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q157
median167
Q3382
95-th percentile838
Maximum860
Range859
Interquartile range (IQR)325

Descriptive statistics

Standard deviation277.80833
Coefficient of variation (CV)1.0193246
Kurtosis-0.26771172
Mean272.54158
Median Absolute Deviation (MAD)137
Skewness1.0619364
Sum7200276
Variance77177.466
MonotonicityNot monotonic
2024-06-24T23:57:10.606597image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 387
 
1.5%
8 352
 
1.3%
1 339
 
1.3%
22 326
 
1.2%
18 309
 
1.2%
30 308
 
1.2%
20 300
 
1.1%
13 271
 
1.0%
815 266
 
1.0%
119 257
 
1.0%
Other values (849) 23304
88.2%
ValueCountFrequency (%)
1 339
1.3%
2 184
0.7%
3 206
0.8%
4 387
1.5%
5 112
 
0.4%
6 36
 
0.1%
7 27
 
0.1%
8 352
1.3%
9 99
 
0.4%
10 95
 
0.4%
ValueCountFrequency (%)
860 1
 
< 0.1%
859 5
 
< 0.1%
858 28
 
0.1%
857 29
 
0.1%
856 11
 
< 0.1%
855 51
0.2%
854 44
0.2%
853 22
 
0.1%
852 73
0.3%
851 1
 
< 0.1%

constructorId
Real number (ℝ)

Distinct211
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.641054
Minimum1
Maximum215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:11.143207image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median25
Q360
95-th percentile204
Maximum215
Range214
Interquartile range (IQR)54

Descriptive statistics

Standard deviation60.89551
Coefficient of variation (CV)1.2267167
Kurtosis0.99669199
Mean49.641054
Median Absolute Deviation (MAD)20
Skewness1.4989382
Sum1311467
Variance3708.2631
MonotonicityNot monotonic
2024-06-24T23:57:12.191813image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 2405
 
9.1%
1 1889
 
7.2%
3 1642
 
6.2%
25 881
 
3.3%
32 871
 
3.3%
15 803
 
3.0%
4 787
 
3.0%
9 754
 
2.9%
18 672
 
2.5%
34 662
 
2.5%
Other values (201) 15053
57.0%
ValueCountFrequency (%)
1 1889
7.2%
2 140
 
0.5%
3 1642
6.2%
4 787
 
3.0%
5 536
 
2.0%
6 2405
9.1%
7 280
 
1.1%
8 78
 
0.3%
9 754
 
2.9%
10 424
 
1.6%
ValueCountFrequency (%)
215 14
 
0.1%
214 146
0.6%
213 166
0.6%
211 76
 
0.3%
210 346
1.3%
209 78
 
0.3%
208 154
0.6%
207 112
 
0.4%
206 109
 
0.4%
205 76
 
0.3%

number
Real number (ℝ)

Distinct129
Distinct (%)0.5%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean18.012683
Minimum0
Maximum208
Zeros34
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:12.470267image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q17
median16
Q324
95-th percentile44
Maximum208
Range208
Interquartile range (IQR)17

Descriptive statistics

Standard deviation15.405758
Coefficient of variation (CV)0.85527279
Kurtosis9.0313311
Mean18.012683
Median Absolute Deviation (MAD)8
Skewness2.3735829
Sum475769
Variance237.33738
MonotonicityNot monotonic
2024-06-24T23:57:12.737828image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 1002
 
3.8%
6 994
 
3.8%
8 993
 
3.8%
16 988
 
3.7%
11 984
 
3.7%
3 983
 
3.7%
14 965
 
3.7%
10 959
 
3.6%
20 957
 
3.6%
5 956
 
3.6%
Other values (119) 16632
63.0%
ValueCountFrequency (%)
0 34
 
0.1%
1 827
3.1%
2 951
3.6%
3 983
3.7%
4 1002
3.8%
5 956
3.6%
6 994
3.8%
7 928
3.5%
8 993
3.8%
9 892
3.4%
ValueCountFrequency (%)
208 1
< 0.1%
136 1
< 0.1%
135 1
< 0.1%
130 1
< 0.1%
129 1
< 0.1%
128 1
< 0.1%
127 1
< 0.1%
126 1
< 0.1%
125 1
< 0.1%
124 1
< 0.1%

grid
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.151255
Minimum0
Maximum34
Zeros1627
Zeros (%)6.2%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:12.993175image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median11
Q317
95-th percentile23
Maximum34
Range34
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.217744
Coefficient of variation (CV)0.64725846
Kurtosis-0.92710449
Mean11.151255
Median Absolute Deviation (MAD)6
Skewness0.19316088
Sum294605
Variance52.095828
MonotonicityNot monotonic
2024-06-24T23:57:13.277881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 1627
 
6.2%
1 1119
 
4.2%
7 1118
 
4.2%
4 1115
 
4.2%
11 1115
 
4.2%
9 1115
 
4.2%
5 1115
 
4.2%
3 1113
 
4.2%
10 1113
 
4.2%
8 1112
 
4.2%
Other values (25) 14757
55.9%
ValueCountFrequency (%)
0 1627
6.2%
1 1119
4.2%
2 1108
4.2%
3 1113
4.2%
4 1115
4.2%
5 1115
4.2%
6 1108
4.2%
7 1118
4.2%
8 1112
4.2%
9 1115
4.2%
ValueCountFrequency (%)
34 1
 
< 0.1%
33 13
 
< 0.1%
32 17
 
0.1%
31 18
 
0.1%
30 19
 
0.1%
29 25
 
0.1%
28 30
 
0.1%
27 46
 
0.2%
26 248
0.9%
25 301
1.1%

position
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct33
Distinct (%)0.2%
Missing10917
Missing (%)41.3%
Infinite0
Infinite (%)0.0%
Mean7.9910334
Minimum1
Maximum33
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:13.547313image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q311
95-th percentile17
Maximum33
Range32
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.8269168
Coefficient of variation (CV)0.60404163
Kurtosis-0.44558663
Mean7.9910334
Median Absolute Deviation (MAD)4
Skewness0.46998992
Sum123877
Variance23.299126
MonotonicityNot monotonic
2024-06-24T23:57:13.810793image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
3 1118
 
4.2%
4 1118
 
4.2%
2 1116
 
4.2%
5 1114
 
4.2%
1 1111
 
4.2%
6 1107
 
4.2%
7 1087
 
4.1%
8 1059
 
4.0%
9 1021
 
3.9%
10 961
 
3.6%
Other values (23) 4690
17.8%
(Missing) 10917
41.3%
ValueCountFrequency (%)
1 1111
4.2%
2 1116
4.2%
3 1118
4.2%
4 1118
4.2%
5 1114
4.2%
6 1107
4.2%
7 1087
4.1%
8 1059
4.0%
9 1021
3.9%
10 961
3.6%
ValueCountFrequency (%)
33 1
 
< 0.1%
32 1
 
< 0.1%
31 1
 
< 0.1%
30 1
 
< 0.1%
29 1
 
< 0.1%
28 1
 
< 0.1%
27 1
 
< 0.1%
26 1
 
< 0.1%
25 1
 
< 0.1%
24 3
< 0.1%

positionText
Categorical

HIGH CORRELATION  MISSING 

Distinct37
Distinct (%)0.2%
Missing9015
Missing (%)34.1%
Memory size206.5 KiB
F
1368 
3
 
1118
4
 
1118
2
 
1116
5
 
1114
Other values (32)
11570 

Length

Max length2
Median length1
Mean length1.3248104
Min length1

Characters and Unicode

Total characters23057
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5

Common Values

ValueCountFrequency (%)
F 1368
 
5.2%
3 1118
 
4.2%
4 1118
 
4.2%
2 1116
 
4.2%
5 1114
 
4.2%
1 1111
 
4.2%
6 1107
 
4.2%
7 1087
 
4.1%
8 1059
 
4.0%
9 1021
 
3.9%
Other values (27) 6185
23.4%
(Missing) 9015
34.1%

Length

2024-06-24T23:57:14.078398image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
f 1368
 
7.9%
3 1118
 
6.4%
4 1118
 
6.4%
2 1116
 
6.4%
5 1114
 
6.4%
1 1111
 
6.4%
6 1107
 
6.4%
7 1087
 
6.2%
8 1059
 
6.1%
9 1021
 
5.9%
Other values (27) 6185
35.5%

Most occurring characters

ValueCountFrequency (%)
1 7542
32.7%
2 2057
 
8.9%
3 1827
 
7.9%
4 1710
 
7.4%
5 1626
 
7.1%
6 1526
 
6.6%
7 1411
 
6.1%
F 1368
 
5.9%
8 1272
 
5.5%
9 1155
 
5.0%
Other values (4) 1563
 
6.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23057
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 7542
32.7%
2 2057
 
8.9%
3 1827
 
7.9%
4 1710
 
7.4%
5 1626
 
7.1%
6 1526
 
6.6%
7 1411
 
6.1%
F 1368
 
5.9%
8 1272
 
5.5%
9 1155
 
5.0%
Other values (4) 1563
 
6.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23057
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 7542
32.7%
2 2057
 
8.9%
3 1827
 
7.9%
4 1710
 
7.4%
5 1626
 
7.1%
6 1526
 
6.6%
7 1411
 
6.1%
F 1368
 
5.9%
8 1272
 
5.5%
9 1155
 
5.0%
Other values (4) 1563
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23057
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 7542
32.7%
2 2057
 
8.9%
3 1827
 
7.9%
4 1710
 
7.4%
5 1626
 
7.1%
6 1526
 
6.6%
7 1411
 
6.1%
F 1368
 
5.9%
8 1272
 
5.5%
9 1155
 
5.0%
Other values (4) 1563
 
6.8%

positionOrder
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.823574
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:14.344599image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median12
Q318
95-th percentile26
Maximum39
Range38
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.682877
Coefficient of variation (CV)0.59912135
Kurtosis-0.4818229
Mean12.823574
Median Absolute Deviation (MAD)6
Skewness0.3971628
Sum338786
Variance59.026598
MonotonicityNot monotonic
2024-06-24T23:57:14.624913image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
3 1118
 
4.2%
4 1118
 
4.2%
2 1117
 
4.2%
11 1116
 
4.2%
5 1115
 
4.2%
6 1115
 
4.2%
7 1115
 
4.2%
8 1115
 
4.2%
9 1114
 
4.2%
10 1113
 
4.2%
Other values (29) 15263
57.8%
ValueCountFrequency (%)
1 1111
4.2%
2 1117
4.2%
3 1118
4.2%
4 1118
4.2%
5 1115
4.2%
6 1115
4.2%
7 1115
4.2%
8 1115
4.2%
9 1114
4.2%
10 1113
4.2%
ValueCountFrequency (%)
39 13
 
< 0.1%
38 17
 
0.1%
37 17
 
0.1%
36 18
 
0.1%
35 29
 
0.1%
34 46
 
0.2%
33 65
0.2%
32 79
0.3%
31 117
0.4%
30 156
0.6%

points
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9477289
Minimum0
Maximum50
Zeros18419
Zeros (%)69.7%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:14.908379image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile10
Maximum50
Range50
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.2874056
Coefficient of variation (CV)2.2012332
Kurtosis11.109091
Mean1.9477289
Median Absolute Deviation (MAD)0
Skewness3.0827107
Sum51457.05
Variance18.381847
MonotonicityNot monotonic
2024-06-24T23:57:15.181234image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 18419
69.7%
2 1109
 
4.2%
4 1095
 
4.1%
6 1075
 
4.1%
1 1050
 
4.0%
3 823
 
3.1%
10 597
 
2.3%
8 458
 
1.7%
9 443
 
1.7%
12 278
 
1.1%
Other values (29) 1072
 
4.1%
ValueCountFrequency (%)
0 18419
69.7%
0.5 6
 
< 0.1%
1 1050
 
4.0%
1.33 3
 
< 0.1%
1.5 17
 
0.1%
2 1109
 
4.2%
2.5 1
 
< 0.1%
3 823
 
3.1%
3.14 1
 
< 0.1%
3.5 1
 
< 0.1%
ValueCountFrequency (%)
50 1
 
< 0.1%
36 1
 
< 0.1%
30 1
 
< 0.1%
26 35
 
0.1%
25 251
1.0%
24 1
 
< 0.1%
20 1
 
< 0.1%
19 22
 
0.1%
18 264
1.0%
16 11
 
< 0.1%

laps
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct172
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.169499
Minimum0
Maximum200
Zeros2519
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:15.487419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q123
median53
Q366
95-th percentile79
Maximum200
Range200
Interquartile range (IQR)43

Descriptive statistics

Standard deviation29.598762
Coefficient of variation (CV)0.64108909
Kurtosis3.6900793
Mean46.169499
Median Absolute Deviation (MAD)17
Skewness0.71087761
Sum1219752
Variance876.08672
MonotonicityNot monotonic
2024-06-24T23:57:15.777198image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2519
 
9.5%
70 958
 
3.6%
53 924
 
3.5%
52 801
 
3.0%
56 796
 
3.0%
57 694
 
2.6%
69 663
 
2.5%
71 628
 
2.4%
55 581
 
2.2%
58 557
 
2.1%
Other values (162) 17298
65.5%
ValueCountFrequency (%)
0 2519
9.5%
1 307
 
1.2%
2 228
 
0.9%
3 199
 
0.8%
4 183
 
0.7%
5 196
 
0.7%
6 183
 
0.7%
7 166
 
0.6%
8 187
 
0.7%
9 178
 
0.7%
ValueCountFrequency (%)
200 123
0.5%
199 4
 
< 0.1%
197 5
 
< 0.1%
196 15
 
0.1%
195 4
 
< 0.1%
194 4
 
< 0.1%
193 7
 
< 0.1%
192 1
 
< 0.1%
191 8
 
< 0.1%
190 2
 
< 0.1%

milliseconds
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7436
Distinct (%)99.5%
Missing18942
Missing (%)71.7%
Infinite0
Infinite (%)0.0%
Mean6211175.8
Minimum207071
Maximum15090540
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:16.087213image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum207071
5-th percentile4784382.6
Q15389775
median5798072
Q36418859
95-th percentile9710080
Maximum15090540
Range14883469
Interquartile range (IQR)1029084

Descriptive statistics

Standard deviation1656493.2
Coefficient of variation (CV)0.26669559
Kurtosis9.4728448
Mean6211175.8
Median Absolute Deviation (MAD)473463
Skewness2.5454826
Sum4.6440962 × 1010
Variance2.7439697 × 1012
MonotonicityNot monotonic
2024-06-24T23:57:16.412646image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14259460 5
 
< 0.1%
10928200 3
 
< 0.1%
12131000 2
 
< 0.1%
5350182 2
 
< 0.1%
6034426 2
 
< 0.1%
8627000 2
 
< 0.1%
13642300 2
 
< 0.1%
5152531 2
 
< 0.1%
4584572 2
 
< 0.1%
5808819 2
 
< 0.1%
Other values (7426) 7453
 
28.2%
(Missing) 18942
71.7%
ValueCountFrequency (%)
207071 1
< 0.1%
209066 1
< 0.1%
209672 1
< 0.1%
211567 1
< 0.1%
214550 1
< 0.1%
217248 1
< 0.1%
218650 1
< 0.1%
219679 1
< 0.1%
222556 1
< 0.1%
223237 1
< 0.1%
ValueCountFrequency (%)
15090540 1
< 0.1%
14977530 1
< 0.1%
14926980 1
< 0.1%
14823600 1
< 0.1%
14779660 1
< 0.1%
14743144 1
< 0.1%
14729991 1
< 0.1%
14726593 1
< 0.1%
14724654 1
< 0.1%
14715501 1
< 0.1%

fastestLap
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct80
Distinct (%)1.0%
Missing18478
Missing (%)69.9%
Infinite0
Infinite (%)0.0%
Mean42.526004
Minimum1
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:16.707168image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q133
median45
Q354
95-th percentile67
Maximum85
Range84
Interquartile range (IQR)21

Descriptive statistics

Standard deviation16.674019
Coefficient of variation (CV)0.39208995
Kurtosis-0.30390997
Mean42.526004
Median Absolute Deviation (MAD)10
Skewness-0.53709397
Sum337699
Variance278.02291
MonotonicityNot monotonic
2024-06-24T23:57:16.974274image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 298
 
1.1%
52 273
 
1.0%
53 272
 
1.0%
51 257
 
1.0%
48 219
 
0.8%
49 214
 
0.8%
55 212
 
0.8%
44 209
 
0.8%
43 204
 
0.8%
54 204
 
0.8%
Other values (70) 5579
 
21.1%
(Missing) 18478
69.9%
ValueCountFrequency (%)
1 10
 
< 0.1%
2 55
0.2%
3 32
0.1%
4 55
0.2%
5 41
0.2%
6 54
0.2%
7 41
0.2%
8 42
0.2%
9 49
0.2%
10 51
0.2%
ValueCountFrequency (%)
85 2
 
< 0.1%
80 3
 
< 0.1%
78 6
 
< 0.1%
77 12
< 0.1%
76 13
< 0.1%
75 16
0.1%
74 21
0.1%
73 5
 
< 0.1%
72 15
0.1%
71 27
0.1%

rank
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct25
Distinct (%)0.3%
Missing18249
Missing (%)69.1%
Infinite0
Infinite (%)0.0%
Mean10.374786
Minimum0
Maximum24
Zeros229
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:17.224131image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median10
Q316
95-th percentile20
Maximum24
Range24
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.1394455
Coefficient of variation (CV)0.591766
Kurtosis-1.08983
Mean10.374786
Median Absolute Deviation (MAD)5
Skewness0.071544962
Sum84762
Variance37.692791
MonotonicityNot monotonic
2024-06-24T23:57:17.471306image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 394
 
1.5%
6 394
 
1.5%
5 394
 
1.5%
1 394
 
1.5%
3 394
 
1.5%
4 394
 
1.5%
10 393
 
1.5%
11 393
 
1.5%
7 393
 
1.5%
9 393
 
1.5%
Other values (15) 4234
 
16.0%
(Missing) 18249
69.1%
ValueCountFrequency (%)
0 229
0.9%
1 394
1.5%
2 394
1.5%
3 394
1.5%
4 394
1.5%
5 394
1.5%
6 394
1.5%
7 393
1.5%
8 393
1.5%
9 393
1.5%
ValueCountFrequency (%)
24 28
 
0.1%
23 43
 
0.2%
22 91
 
0.3%
21 122
 
0.5%
20 278
1.1%
19 335
1.3%
18 374
1.4%
17 384
1.5%
16 390
1.5%
15 391
1.5%

fastestLapSpeed
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7443
Distinct (%)93.7%
Missing18478
Missing (%)69.9%
Infinite0
Infinite (%)0.0%
Mean203.78036
Minimum89.54
Maximum257.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:17.740090image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum89.54
5-th percentile158.686
Q1193.253
median204.808
Q3217.01
95-th percentile236.841
Maximum257.32
Range167.78
Interquartile range (IQR)23.757

Descriptive statistics

Standard deviation21.375336
Coefficient of variation (CV)0.10489399
Kurtosis0.99185985
Mean203.78036
Median Absolute Deviation (MAD)11.846
Skewness-0.59712927
Sum1618219.9
Variance456.90498
MonotonicityNot monotonic
2024-06-24T23:57:18.042076image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207.069 4
 
< 0.1%
201.33 3
 
< 0.1%
217.668 3
 
< 0.1%
202.871 3
 
< 0.1%
204.946 3
 
< 0.1%
200.091 3
 
< 0.1%
200.363 3
 
< 0.1%
222.592 3
 
< 0.1%
210.022 3
 
< 0.1%
209.244 3
 
< 0.1%
Other values (7433) 7910
29.9%
(Missing) 18478
69.9%
ValueCountFrequency (%)
89.54 1
< 0.1%
91.61 1
< 0.1%
100.615 1
< 0.1%
101.399 1
< 0.1%
101.884 1
< 0.1%
108.41 1
< 0.1%
112.116 1
< 0.1%
117.753 1
< 0.1%
118.872 1
< 0.1%
121.027 1
< 0.1%
ValueCountFrequency (%)
257.32 1
< 0.1%
256.324 1
< 0.1%
255.874 1
< 0.1%
255.014 1
< 0.1%
254.861 1
< 0.1%
253.874 1
< 0.1%
253.566 1
< 0.1%
252.794 1
< 0.1%
252.77 1
< 0.1%
252.604 1
< 0.1%

statusId
Real number (ℝ)

HIGH CORRELATION 

Distinct137
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.363261
Minimum1
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size206.5 KiB
2024-06-24T23:57:18.346067image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median10
Q314
95-th percentile81
Maximum141
Range140
Interquartile range (IQR)13

Descriptive statistics

Standard deviation26.11787
Coefficient of variation (CV)1.504203
Kurtosis4.0978449
Mean17.363261
Median Absolute Deviation (MAD)9
Skewness2.2200757
Sum458720
Variance682.14311
MonotonicityNot monotonic
2024-06-24T23:57:18.646322image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 7472
28.3%
11 3954
15.0%
5 2022
 
7.7%
12 1600
 
6.1%
3 1057
 
4.0%
81 1025
 
3.9%
4 843
 
3.2%
6 809
 
3.1%
20 792
 
3.0%
13 731
 
2.8%
Other values (127) 6114
23.1%
ValueCountFrequency (%)
1 7472
28.3%
2 145
 
0.5%
3 1057
 
4.0%
4 843
 
3.2%
5 2022
 
7.7%
6 809
 
3.1%
7 321
 
1.2%
8 214
 
0.8%
9 138
 
0.5%
10 316
 
1.2%
ValueCountFrequency (%)
141 1
 
< 0.1%
140 4
 
< 0.1%
139 3
 
< 0.1%
138 1
 
< 0.1%
137 2
 
< 0.1%
136 1
 
< 0.1%
135 1
 
< 0.1%
132 5
 
< 0.1%
131 41
0.2%
130 58
0.2%

Interactions

2024-06-24T23:57:01.878974image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:00.904934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:06.943871image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:11.587951image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:15.651416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:20.458314image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:24.206857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:28.258399image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:33.099780image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:36.940753image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:40.902818image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:45.758521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:49.540050image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:53.467294image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:57.838754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:02.141075image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:01.357250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:07.205040image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:11.852345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:16.019070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:20.687744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:24.461234image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:28.575018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:33.358351image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:37.182004image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:41.185108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:46.011980image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:49.779914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:53.699219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:58.245538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:02.389834image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:01.990045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:07.434331image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:12.129191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:16.396498image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:20.914307image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:24.722974image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:28.938883image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:33.620342image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:37.403108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:41.433550image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:46.275581image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:49.998438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:53.933799image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:58.609141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:02.622572image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:02.595828image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:07.672704image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:12.363408image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:16.758428image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:21.167217image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:24.969082image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:29.320107image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:33.866232image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:37.615647image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:41.677235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:46.505538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:50.260115image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:54.173620image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:58.885574image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:02.882034image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:03.132857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:07.905758image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:12.624967image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:17.085588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:21.380296image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:25.251935image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:29.622673image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:34.126864image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:37.865865image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:41.995742image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:46.734663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:50.493591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:54.414089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:59.146644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:03.127848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:03.676291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:08.174831image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:12.863786image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:17.438590image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:21.599994image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:25.478239image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:29.998054image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:34.381668image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:38.085577image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:42.350792image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:46.989315image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:50.711557image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:54.643166image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:59.395540image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:03.382985image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:04.506666image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:08.424822image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:13.130208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:17.816062image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:21.851795image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:25.724177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:30.370728image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:34.653790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:38.339058image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:42.667075image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:47.271851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:50.942343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:54.880540image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:59.648110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:03.626773image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:04.888289image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:08.673744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:13.384523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:18.464691image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:22.160070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:25.970313image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:30.725357image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:34.918311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:38.582991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:43.016546image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:47.527698image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:51.171116image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:55.134962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:59.883563image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:03.918633image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:05.183668image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:08.928188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:13.637131image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:18.722974image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:22.428695image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:26.249335image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:31.125066image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:35.198613image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:39.175447image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:43.372615image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:47.759125image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:51.418486image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:55.372156image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:00.146146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:04.178738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:05.428149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:10.078733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:13.887738image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:18.958296image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:22.664099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:26.509892image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:31.513248image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:35.441687image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:39.401272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:43.697644image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:48.003439image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:51.638041image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:55.678810image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:00.377397image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:04.439978image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:05.687959image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:10.346953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:14.163177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:19.241806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:22.920304image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:26.778229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:31.866108image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:35.700378image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:39.648868image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:44.047479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:48.296138image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:51.845701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:56.009442image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:00.618733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:04.734406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:05.945658image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:10.610480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:14.413496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:19.493638image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:23.220007image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:27.316219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:32.132092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:35.964900image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:39.912405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:44.456430image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:48.551052image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:52.082380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:56.412570image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:00.890188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:05.056522image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:06.180565image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:10.838475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:14.641587image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:19.713711image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:23.446904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:27.539629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:32.360461image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:36.220393image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:40.168629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:44.768621image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:48.788769image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:52.320285image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:56.753327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:01.122235image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:05.407505image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:06.421191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:11.069512image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:14.920495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:19.938607image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:23.689299image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:27.754728image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:32.599807image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:36.431443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:40.388855image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:45.139809image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:49.028481image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:52.550373image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:57.114405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:01.361045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:05.744269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:06.679012image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:11.332788image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:15.267220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:20.208859image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:23.933875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:28.000267image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:32.852348image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:36.677211image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:40.635055image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:45.503013image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:49.304394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:52.793418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:56:57.473100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-06-24T23:57:01.607636image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-06-24T23:57:18.919213image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
constructorIddriverIdfastestLapfastestLapSpeedgridlapsmillisecondsnumberpointspositionpositionOrderpositionTextraceIdrankresultIdstatusId
constructorId1.0000.3190.030-0.0220.173-0.1080.1680.286-0.2190.1880.2030.2050.3250.1570.3020.261
driverId0.3191.0000.0700.0540.069-0.0020.1880.253-0.0790.1580.0680.1710.7030.1680.6640.104
fastestLap0.0300.0701.000-0.039-0.0340.5880.1710.0280.2110.005-0.2640.0170.173-0.2590.178-0.169
fastestLapSpeed-0.0220.054-0.0391.000-0.133-0.230-0.789-0.0250.119-0.107-0.1660.0490.123-0.1960.116-0.155
grid0.1730.069-0.034-0.1331.0000.0460.0070.210-0.4000.6740.2180.335-0.0300.574-0.0250.171
laps-0.108-0.0020.588-0.2300.0461.0000.409-0.1240.420-0.136-0.6830.3200.078-0.1890.086-0.291
milliseconds0.1680.1880.171-0.7890.0070.4091.0000.023-0.027-0.085-0.0860.0750.1170.0980.100-0.025
number0.2860.2530.028-0.0250.210-0.1240.0231.000-0.2200.2970.2490.1320.1840.2200.1700.232
points-0.219-0.0790.2110.119-0.4000.420-0.027-0.2201.000-0.857-0.7830.4130.136-0.6090.153-0.621
position0.1880.1580.005-0.1070.674-0.136-0.0850.297-0.8571.0001.0000.9990.0950.7160.1160.582
positionOrder0.2030.068-0.264-0.1660.218-0.683-0.0860.249-0.7831.0001.0000.747-0.0600.629-0.0660.567
positionText0.2050.1710.0170.0490.3350.3200.0750.1320.4130.9990.7471.000-0.066-0.146-0.0840.269
raceId0.3250.7030.1730.123-0.0300.0780.1170.1840.1360.095-0.060-0.0661.000-0.0610.968-0.065
rank0.1570.168-0.259-0.1960.574-0.1890.0980.220-0.6090.7160.629-0.146-0.0611.000-0.0620.526
resultId0.3020.6640.1780.116-0.0250.0860.1000.1700.1530.116-0.066-0.0840.968-0.0621.000-0.093
statusId0.2610.104-0.169-0.1550.171-0.291-0.0250.232-0.6210.5820.5670.269-0.0650.526-0.0931.000

Missing values

2024-06-24T23:57:06.269233image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-06-24T23:57:07.159674image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-06-24T23:57:07.925549image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

resultIdraceIddriverIdconstructorIdnumbergridpositionpositionTextpositionOrderpointslapsmillisecondsfastestLaprankfastestLapSpeedstatusId
01181122.011.01110.0585690616.039.02.0218.3001
1218223.052.0228.0585696094.041.03.0217.5861
2318337.073.0336.0585698779.041.05.0216.7191
3418445.0114.0445.0585707797.058.07.0215.4641
45185123.035.0554.0585708630.043.01.0218.3851
5618638.0136.0663.057NaN50.014.0212.97411
67187514.0177.0772.055NaN54.08.0213.2245
7818861.0158.0881.053NaN20.04.0217.1805
8918924.02NaNNaN90.047NaN15.09.0215.1004
9101810712.018NaNNaN100.043NaN23.013.0213.1663
resultIdraceIddriverIdconstructorIdnumbergridpositionpositionTextpositionOrderpointslapsmillisecondsfastestLaprankfastestLapSpeedstatusId
2640926415112780721027.01011.011110.062NaN3.020.0216.30811
2641026416112782521020.01812.012120.062NaN58.012.0218.15311
264112641711278172153.0913.013130.062NaN13.019.0216.65511
2641226418112783921431.01214.014140.062NaN37.016.0217.36111
264132641911278551524.01715.015150.062NaN37.013.0218.13411
2641426420112784221410.01516.016160.062NaN10.017.0217.18311
2641526421112785832.01917.017170.062NaN55.014.0217.56211
264162642211278221577.01618.018180.062NaN11.018.0216.95911
26417264231127411714.02019.019190.062NaN62.02.0223.68911
26418264241127848323.014NaNNaN200.051NaN48.015.0217.44231